Abstract: In an illustrative embodiment, systems and methods for performing cascading matching of data records from disparate data sources comprise identifying matches using at least one uniquely identifying data field and at least one additional data field shared by a first data set and a second data set. Potential matches may be resolved through calculating differences between one or more shared data fields of a matched data record of the first data set and both a first matched record and a second matched record of the second data set, and determining a best match through analyzing the calculated differences. Unmatched records may be iteratively matched using a different uniquely identifying data field and/or different at least one additional data field(s).

Abstract: The present disclosure relates to systems and methods for optimizing benefits plan options offered by an organization through balancing derived population preferences with organizational preferences by analyzing historical selections made by individuals. Census data dividing members of an organization into census divisions may be applied to machine learning algorithm(s) to derive estimated selection preferences of the members. Using selection preferences, costs of various product offering scenarios and overall member satisfaction estimates of the scenarios may be calculated. Product offering scenarios meeting member preference criteria and organizational budget criteria may be presented for review.

Abstract: In an illustrative embodiment, methods and systems for identifying prospective new clients based upon review of current clients include accessing a book of business of a user of a transactional platform to identify current clients, identifying, key terms relevant to each of the clients, automatically performing Internet searches, each search using different groupings of the key terms, automatically deriving from web sites of the search results information regarding a number of prospects, and presenting prospect information to the user. The key terms may be identified through performing web searches and web scraping of online information related to the current clients. The clients may be categorized based upon organizational attributes prior to searching. An initial set or sets of key terms may be filtered through performing a number of data analyses on the key terms.

Abstract: In an illustrative embodiment, systems and methods for predicting subscriber churn include machine learning algorithm(s) for classifying the subscriber's decision to stay with the present subscription provider or to switch (churn) to a new provider. The machine learning algorithms may include a logistic regression/neural network for modeling churn propensity in subscribers. The churn risk analysis systems and methods may identify a group of subscribers most likely to churn. Further, the churn risk analysis systems and methods may identify a group of subscribers least likely to churn. The identified subscribers may be presented to a representative of the subscription provider, for example through a user interface.

Abstract: In an illustrative embodiment, systems and methods for automatically identifying peer organizations of a subject organization within a transactional platform identify peer organizations of the subject organization by accessing characteristic features and transactional features of the subject organization, providing a portion of the features to similarity analysis models, and obtaining, through executing the models, predicted peer organizations. The predicted peers may be presented to a user arranged in priority order with some peer features of the respective organization and a control for selecting the respective peer. The user may select a subset of the predicted peers for use in comparison metrics.

Abstract: In an illustrative embodiment, systems and methods for performing cascading matching of data records from disparate data sources comprise identifying matches using at least one uniquely identifying data field and at least one additional data field shared by a first data set and a second data set. Potential matches may be resolved through calculating differences between one or more shared data fields of a matched data record of the first data set and both a first matched record and a second matched record of the second data set, and determining a best match through analyzing the calculated differences. Unmatched records may be iteratively matched using a different uniquely identifying data field and/or different at least one additional data field(s).

Abstract: The present disclosure relates to systems and methods for optimizing benefits plan options offered by an organization through balancing derived population preferences with organizational preferences by analyzing historical selections made by individuals. Census data dividing members of an organization into census divisions may be applied to machine learning algorithm(s) to derive estimated selection preferences of the members. Using selection preferences, costs of various product offering scenarios and overall member satisfaction estimates of the scenarios may be calculated. Product offering scenarios meeting member preference criteria and organizational budget criteria may be presented for review.

Abstract: In an illustrative embodiment, systems and methods for calculating risk scores for locations potentially affected by catastrophic events include receiving a risk score request for a location, the risk score request including a request for assessment of risk exposure related to a type of catastrophic event. Based on the type of catastrophic event, a data compression algorithm may be applied to a catastrophic risk model representing amounts of perceived risk to an area surrounding the location. In response to receiving the risk score request, a risk score for the location may be calculated that corresponds to a weighted estimation of one or more data points in a compressed catastrophic risk model. A risk score user interface screen may be generated in real-time to present the catastrophic risk score and one or more corresponding loss metrics for the location due to a potential occurrence of the type of catastrophic event.

Abstract: In an illustrative embodiment, methods and systems for identifying prospective new clients based upon review of current clients include accessing a book of business of a user of a transactional platform to identify current clients, identifying, key terms relevant to each of the clients, automatically performing Internet searches, each search using different groupings of the key terms, automatically deriving from web sites of the search results information regarding a number of prospects, and presenting prospect information to the user. The key terms may be identified through performing web searches and web scraping of online information related to the current clients. The clients may be categorized based upon organizational attributes prior to searching. An initial set or sets of key terms may be filtered through performing a number of data analyses on the key terms.

Abstract: The present disclosure relates to methods and systems for accelerating the development and distribution of data science workloads, including a consistent, portable and pre-configured data science workspace for development of data science containers allowing for the creation of a standardized, modular and reusable library of data science containers that can be maintained, extended and reused in a clear and repeatable manner. The containers may be submitted to a build and deployment process that ensures consistency across multiple environments in terms of the application code and the operating system environment. Runtime execution may be managed through the authoring of definitions which detail aspects of how the workload should operate within a certain environment.

Abstract: In an illustrative embodiment, methods and systems for cybersecurity assessment of an organization's technology infrastructure include identifying features of the technology infrastructure and automatically generating a threat profile relevant to both the technology infrastructure and the organization's business (and/or business objectives), where the threat profile includes potential threat actors and threat scenarios applicable to the technology infrastructure. The methods and systems may include evaluating cybersecurity controls of the organization's technology infrastructure in light of the threat profile to identify and rate vulnerabilities within the technology infrastructure.

Abstract: In an illustrative embodiment, systems and methods for calculating risk scores for locations potentially affected by catastrophic events include receiving a risk score request for a location, the risk score request including a request for assessment of risk exposure related to a type of catastrophic event. Based on the type of catastrophic event, a data compression algorithm may be applied to a catastrophic risk model representing amounts of perceived risk to an area surrounding the location. In response to receiving the risk score request, a risk score for the location may be calculated that corresponds to a weighted estimation of one or more data points in a compressed catastrophic risk model. A risk score user interface screen may be generated in real-time to present the catastrophic risk score and one or more corresponding loss metrics for the location due to a potential occurrence of the type of catastrophic event.

Abstract: In an illustrative embodiment, an automated system provides for generating product recommendations for clients. The system may include computing systems and devices for receiving a client intake information with product preferences, member demographic information, and current product information, and in response, generating product offerings including at least a portion representing variations of the current product. The member demographic information may be consolidated into census divisions that are each associated with a category of the member demographic information, and probabilities of selecting the product offerings may be calculated for each of the census divisions. The product offerings may be presented in a user interface with optimization scores that are a function of the probability of selecting the product offerings as well as provider financial goals, employee perception goals, and market competitiveness goals.

Abstract: In an illustrative embodiment, methods and systems for cybersecurity assessment of an organization's technology infrastructure include identifying features of the technology infrastructure and automatically generating a threat profile relevant to both the technology infrastructure and the organization's business (and/or business objectives), where the threat profile includes potential threat actors and threat scenarios applicable to the technology infrastructure. The methods and systems may include evaluating cybersecurity controls of the organization's technology infrastructure in light of the threat profile to identify and rate vulnerabilities within the technology infrastructure.

Abstract: In an illustrative embodiment, systems and methods for determining exposure include detecting, based on received data from external entities, an occurrence of a catastrophic event. Responsive to detecting the occurrence, a first matrix is generated indicating features of one or more properties within a vicinity of the catastrophic event, and a second matrix is generated representing characteristics of the catastrophic event. Using the first matrix and the second matrix, a convolution calculation matrix is calculated indicating amounts of correspondence between the first matrix and the second matrix. In real time, in response to detecting the occurrence of the catastrophic event, risk exposure information is presented to at least one remote computing system associated with at least one property of the plurality of properties, where the risk exposure data relates to the amount of correspondence between the first matrix and the second matrix in reference to the at least one property.

Abstract: Audit performance systems and methods can be used to provide objective assessment of the performance of claim administrators. Data from audits performed by one or more insurance broker consultants can be input into the audit performance system, and analyzed, to generate reports that compare the performance of a selected claim administrator to an industry standard level of performance or to one or more other claim administrators.

Abstract: In an illustrative embodiment, systems and methods for identifying properties affected or at risk of being affected by geohazards include obtaining geospatial data representing geographic features and associated geohazard risk with a portion of the features, applying, based on a storage size of the geospatial data, a shape approximation algorithm to geographic shape representations of a geographic area within the geospatial data to reduce the storage size, mapping, to the geospatial data, property data representing a number of manmade features, and adjusting, based on periodically released geospatial data updates accessed from one or more hazard data providers, the geospatial data to incorporate a time element mapping modifications to a portion of elements in the geospatial data, where the resultant geospatial data is maintained in a database for querying to identify impact of geohazards upon property values of a portion of the manmade features.

Abstract: In an illustrative embodiment, methods and systems for identifying prospective new clients based upon review of current clients include accessing a book of business of a user of a transactional platform to identify current clients, identifying, key terms relevant to each of the clients, automatically performing Internet searches, each search using different groupings of the key terms, automatically deriving from web sites of the search results information regarding a number of prospects, and presenting prospect information to the user. The key terms may be identified through performing web searches and web scraping of online information related to the current clients. The clients may be categorized based upon organizational attributes prior to searching. An initial set or sets of key terms may be filtered through performing a number of data analyses on the key terms.

Abstract: In an illustrative embodiment, systems and methods for generating data metrics and relationship analysis from an organization's electronic communications archives include pre-processing the electronic communications into a consistent, workable format, including filtering the data to remove irrelevant messages. Machine learning models may be applied to support automatic identification of relevant message content for data analytics. The systems and methods may link the electronic communications with transaction records of a transactional platform and analyze the communications traffic in view of transactional patterns and outcomes. Communications between parties may be analyzed to identify timings and patterns, plus correlations between electronic communication patterns and business outcomes.

Abstract: In an illustrative embodiment, systems and methods for performing cascading matching of data records from disparate data sources comprise identifying matches using at least one uniquely identifying data field and at least one additional data field shared by a first data set and a second data set. Potential matches may be resolved through calculating differences between one or more shared data fields of a matched data record of the first data set and both a first matched record and a second matched record of the second data set, and determining a best match through analyzing the calculated differences. Unmatched records may be iteratively matched using a different uniquely identifying data field and/or different at least one additional data field(s).